Triple
T18037804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FR-63 |
E431555
|
entity |
| Predicate | hasAlphabeticComponent |
P17387
|
FINISHED |
| Object | FR |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: FR | Statement: [FR-63, hasAlphabeticComponent, FR]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlphabeticComponent Context triple: [FR-63, hasAlphabeticComponent, FR]
-
A.
hasComponentCharacter
Indicates that one entity includes another entity as a constituent character or symbolic component.
-
B.
alphabeticPartRepresents
Indicates that the alphabetic portion of an identifier, code, or label stands for or denotes a particular concept, category, or entity.
-
C.
hasLetter
chosen
Indicates that one entity contains, includes, or is associated with a specific letter or character.
-
D.
usesAlphabet
Indicates that one entity employs or is written using the alphabet or writing system associated with another entity.
-
E.
hasCodeLetters
Indicates that an entity is associated with, or represented by, a specific sequence of letters used as its code or identifier.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4be3bc3208190a6db569e79f06232 |
completed | April 19, 2026, 11:36 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:25 a.m.